“Differences in Virtual and Physical Head Pose” Predict Cybersickness When Naturalistic Head-Movements are Made in VR
Bibliographic record
Abstract
When we move during virtual reality (VR) display lag produces Differences in our Virtual and Physical head pose (DVP). Research suggests that DVP can be used to predict cybersickness during head-mounted display (HMD) based VR. However, these studies always had participants make unusual (continuous oscillatory) head-movements. This study examined whether DVP also predicts cybersickness during more typical VR conditions. After assessing their susceptibility to real-world motion sickness (using the MSSQ-Revised), 67 participants repeatedly moved their heads to “target” objects that appeared inside a virtual room (under different experimentally imposed display lags). We found that cybersickness was more likely and severe when: (1) participants had higher MSSQ scores; (2) the spatial magnitudes and the detrended fluctuation analysis α values of their DVP increased. Based on these findings we believe that real-time estimates of the DVP could be used to warn users about the imminent onset of sickness during consumer HMD VR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".